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Found 5 papers, 1 papers with code
Anatomy of Neural Language Models
Transformers have been at the heart of these advancements where the cutting-edge transformer-based Language Models (LMs) have led to new state-of-the-art results in a wide spectrum of applications.
Leveraging triplet loss and nonlinear dimensionality reduction for on-the-fly channel charting
Channel charting is an unsupervised learning method that aims at mapping wireless channels to a so-called chart, preserving as much as possible spatial neighborhoods.
Deep learning for location based beamforming with NLOS channels
Massive MIMO systems are highly efficient but critically rely on accurate channel state information (CSI) at the base station in order to determine appropriate precoders.
Online unsupervised deep unfolding for MIMO channel estimation
Channel estimation is a difficult problem in MIMO systems.
Channel estimation: unified view of optimal performance and pilot sequences
In this setting, the problem of designing optimal pilot sequences of smallest possible size is studied for any parametric channel model.
